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24th April 2026 Languages English English English The Department of Electronic Systems has a vacancy for a PhD Candidate in Distributed Machine Learning Apply for this job See advertisement This is
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, materials science, and physics. Supported by 19 countries, the ESRF is an equal opportunity employer and encourages diversity. Context & Job description Thesis subject: Machine Learning for Neutron
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. Joerg Hoffmann at University of Saarland. 2) 1-2 PhD students working with Prof. Hendrik Blockeel and/or Prof. Jesse Davis on the topic of developing novel approaches for learning, compressing, and
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biomedical research. Your profile Master's degree in computer science or related discipline Experience with Python and recent deep learning frameworks (e.g. Pytorch, MONAI) Strong interest in image analysis
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PhD candidate on Interprofessional Learning and Team Resilience through the Electronic Health Record
13 Mar 2026 Job Information Organisation/Company Maastricht University (UM) Research Field Educational sciences » Education Educational sciences » Learning studies Researcher Profile First Stage
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their passion and determination? We are currently seeking a/an University assistant predoctoral - PhD Position in Graph Learning 39 Faculty of Computer Science Startdate: 01.05.2026 | Working hours: 30
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of material behavior to the development of the material to the finished component. PhD position on physics-based machine learning modeling for materials and process design Reference code: 980 - 2026/WD 1
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contribution of the PhD will be the derivation of multilayered approaches for motion planning and control based on the XS-Graphs, where both model-based and learning-based solutions are foreseen. This includes
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dedicated to advancing cognitive robotics. The network trains early-stage researchers to develop robots that can interact, learn, and adapt in real-world environments while ensuring quality, safety, and
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for part-time employment. Starting date: 27.03.2026 Job description:PhD position on physics-based machine learning modeling for materials and process design Reference code: 2026/WD 1 Commencement date